A tree based representation for effective pattern discovery from multimedia documents

Abstract

The growing amount of multimedia documents demanded the efficient knowledge discovery systems. The efficacy of the knowledge discovery systems is influenced by the representation of multimedia documents. The suitable multimedia document representation acts as a platform for multimedia mining tasks. In this paper, a Multimedia Suffix Tree Document model (MSTD) is presented to represent the multimedia documents in a tree based structure. The MSTD model discovers the useful patterns embedded in the multimedia documents and reduces the search time thereby aiding the multimedia mining methods. It provides the complete information of the multimedia documents in one structure. In order to evaluate the proficiency of the proposed MSTD model, the MSTD model based mining methods are proposed. The experiments are conducted with three multimodal multimedia document datasets. The experimental analysis of the proposed methods reveal the significance of MSTD representation for multimedia documents in achieving the significant performance of multimedia mining tasks. 2016 Elsevier B.V.